Senior Director, Data & AI – Americas
DP WorldAbout the role
The Senior Director, Data & AI is responsible for building and operating regional data and artificial intelligence capabilities that deliver measurable business value across DP World Americas.
This role owns the practical application of data, analytics, and AI, working closely with business leaders, Technology domain leaders, and the Regional Transformation team to identify, prioritize, and operationalize real-world use cases that improve decision-making, efficiency, and performance.
The focus of this role is disciplined execution and adoption, supported by targeted experimentation and test-and-learn approaches that are explicitly tied to measurable business outcomes. Data and AI are capabilities that are key enablers and embedded into business workflows and transformation initiatives.
KEY ACCOUNTABILITIES
DATA AND AI CAPABILITY OWNERSHIP
- Establish and own the regional Data & AI capability for the Americas, aligned with Group standards and strategy
- Define a clear, pragmatic roadmap for analytics and AI adoption focused on business outcomes
- Ensure data and AI capabilities are scalable, secure, and fit for purpose in partnership with Core Platforms and Enterprise Systems
BUSINESS USE CASE DEVELOPMENT AND ADOPTION
- Partner with business leaders and the Regional Transformation team / Business PMO across Ports & Terminals, Contract Logistics, Freight Forwarding, and Corporate functions to identify high-value data and AI use cases
- Prioritize use cases based on business impact, feasibility, and readiness — not technology novelty
- Lead delivery of data and AI solutions into production environments and operational workflows
- Drive adoption by ensuring solutions are usable, understood, and embedded into day-to-day decision-making
TRANSFROMATION PARTNERSHIP AND VALUE DELIVERY
- Work closely with the Regional Transformation team and Business PMO (Carey Boone’s organization) to align data and AI initiatives to approved transformation programs and business priorities
- Support transformation initiatives by embedding data, analytics, and AI capabilities into defined operating model changes and business outcomes
- Ensure data and AI initiatives flow through established transformation governance, prioritization, and value-tracking mechanisms
- Partner on benefit realization by defining measurable outcomes and supporting adoption within transformation initiatives
ANALYTICS AND REPORTING ENABLEMENT
- Consolidate and mature regional analytics and reporting capabilities, including dashboards and self-service analytics
- Establish standards for data definitions, metrics, and reporting consistency in coordination with business stakeholders
- Ensure analytics solutions support operational, commercial, and executive decision-making
APPLIED AI AND ADVANCED ANALYTICS
- Own the regional application of AI and advanced analytics, including predictive, optimization, and automation use cases
- Translate business problems into practical data and AI solutions in collaboration with domain experts
- Ensure AI solutions are explainable, governed, and aligned with regulatory and ethical expectations
- Maintain a disciplined, outcome-driven approach to AI delivery and usage
DATA GOVERNANCE AND QUALITY (REGIONAL EXECUTION)
- Partner with Group and Enterprise teams to execute data governance, quality, and stewardship practices in the region
- Ensure data used for analytics and AI is reliable, trusted, and appropriate for decision-making
- Support compliance with data privacy, security, and regulatory requirements
COLLABORATION AND ENABLEMENT
- Work closely with Core Platforms to ensure appropriate infrastructure, tooling, security, and operational support for data and AI workloads
- Partner with Enterprise Systems and domain Technology leaders to integrate data and AI solutions into existing platforms
- Enable business and Technology teams to responsibly consume and extend data and AI capabilities
LEADERSHIP AND TEAM DEVELOPMENT
- Build and lead a small, high-impact regional team focused on analytics, data engineering, and applied AI
- Develop internal capability through coaching, standards, and reusable delivery patterns
- Use partners selectively to acce
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